Big Data Examples: 6 Ways Big Data Can Change Your Business | Coursera

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Learn about big data and discover how it can change your business by exploring six big data examples. Then, get tips for building a more data-driven work culture in your business.
Big data examples help businesses and organizations make data-driven decisions in areas such as supply chain management and customer service.
Characteristics that qualify data as “big data” include its volume, value, veracity, variety, and velocity.
Big data presents opportunities to lower costs through predictive analytics.
You can get more out of your data by establishing a strategy with your big data team and clearly defining what you want to learn from your data.
Explore big data examples and how it can help you improve your business. If you’re ready to start building in-demand skills in big data, Big Data Specialization from the University of San Diego can help you learn to extract value from data sets and apply insights to solve real-world problems using tools like regression analysis and classification algorithms.
The term "big data" refers to large amounts of data that traditional data analysis methods and tools cannot analyze, process, or store. Fortunately, modern approaches can help companies evaluate their big data to gain business insights and improve their operations. To better understand big data, let’s look at its characteristics.
Big data plays a big role in everyday life, often behind the scenes. Many of the applications on your mobile phone or other devices rely on big data, from the personalized recommendations you might see on your Netflix or Amazon accounts to the traffic patterns on your GPS applications. If you have ever used a virtual assistant like Amazon Alexa, this technology takes big data one step further with natural language processing, which uses big data analytics to understand and respond to your voice commands.
Five characteristics separate big data from traditional data. For easy recall, all five start with the letter V. They are:
Volume: Big data refers to large data sets, usually containing a million rows of data or more.
Value: The term "big" also refers to the value data provides to an organization.
Veracity: Data has value to organizations only when it is high-quality and comes from reliable sources.
Variety: Big data contains a wide array of data types from varied sources.
Velocity: Big data processes quickly, so companies can use it when they need it.
Big data provides numerous benefits to businesses. Here are six examples of how big data may change yours:
Traditionally, organizational leaders made business decisions based on their experience and intuition. These days, however, business intelligence and data analysis play crucial roles in developing business insights that guide both short and long-term decision-making within organizations. Company leaders use big data analytics to examine past business performance or patterns to make the kind of data-driven decisions needed for future success.
Big data allows companies to examine sales, market trends, employee performance, and more. This type of tracking boosts operational efficiency because it helps companies improve sales strategies, track work processes, and let managers know how many employees and inventory they may need during a particular time period. Overall, big data allows for better and more efficient workflows.
Companies are able to gather data when customers shop online, write product reviews, or share buying experiences on social media. The data gathered and analyzed helps businesses better target customers to deliver more enjoyable buying experiences and improve their product offerings. By evaluating customer feedback using sentiment analysis, you can also learn what customers think about your brand and which products or services are of the greatest interest to them based on their age, gender, or geographical location.
Customers typically return to companies that deliver quality products at reasonable prices on time. Companies can achieve that with the help of great supply chain management. Big data helps ensure good supply chain management by:
Using inventory management methods to ensure product availability
Tracking sales to identify what times of the week, month, or year sales increase or decrease
Using maintenance predictive analytics to keep manufacturing equipment working properly
Using GPS data to identify the most efficient delivery routes
Analyzing GPS systems to reroute impeded delivery routes
Identifying the exact location of shipped products to ensure accurate delivery times
Hear more about how data analytics can be used to improve supply chain management in this lecture from Unilever's Supply Chain Data Analyst Professional Certificate:
Good supply chain management is a key example of how companies lower costs using big data. Factors that improve the supply chain, like predictive maintenance and optimized delivery routes, save companies money. Companies also reduce costs when they can predict how much inventory to have on hand and when they need to produce or buy more.
Some additional ways companies can lower costs with big data include:
Data-driven decisions can reduce the amount of money spent on unsuccessful business strategies.
Data analysis helps single out job candidates who fit the company well and might stay longer.
Big data provides automation for simple tasks in the workplace, allowing employees to concentrate on more complex work.
Big data allows automatic shipment logging so employees can instantly locate products in the warehouse.
Digitized documents, reports, contracts, and other important records lower paper costs and allow quick and centralized access for company employees.
If you own a bank or credit card company, big data can be used to detect fraudulent charges with the help of machine learning algorithms. These algorithms analyze patterns in customer accounts for unusual activity. This process proves so accurate that you can